Artificial Intelligence & datacenters: another threat to nature

ECO article
75
Date

by Ana Di Pangracio (FARN) & Antje Lorch (Ecoropa)

AI is destroying biodiversity through its datacenters: through their water, energy and land use, their greenhouse gas emissions, their increase of local temperatures; their demand for critical minerals and the electronic waste they are producing. Their extraction and processing can contribute to biodiversity loss, ecosystem degradation, pollution and violations of human rights, particularly in countries of the Global South.

These impacts cannot be overlooked in a Convention committed to addressing the underlying drivers of biodiversity loss and transforming unsustainable production and consumption patterns.

The use of AI also raises serious questions about corporate concentration, technological dependency, unequal access to information, and the use of data and knowledge, including that of Indigenous Peoples and local communities.

AI is offered as a tool for biodiversity evaluation, monitoring and reporting, but technological optimism must not replace precaution, independent scrutiny, democratic oversight, and accountability.

Any discussion of AI at the CBD process should consider its entire lifecycle, its implications for human rights, and its compatibility with the goals of the KMGBF. Protecting biodiversity requires more than smarter technologies. It requires confronting the economic and political systems driving ecological destruction.

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Data centers as infrastructure

Source: Environmental Cost of AI's Energy Use: Carbon, Water and Land Footprints.  United Nations University Institute for Water, Environment and Health (2026)

  • In 2025, global data centers were estimated to consume 448 TWh of electricity. If data centers’ electricity use were considered a country, it would have ranked 11th globally by electricity consumption.
  • The energy consumed by data centers in 2025 was enough to supply the annual residential electricity needs of the entire population of Sub-Saharan Africa, 1.3 billion people, for 2.6 years.
  • Data centers’ electricity use in 2025 had a carbon footprint of 189 million tonnes of CO2e, which would require 3.2 billion tree seedlings grown over 10 years to offset, roughly the total number of trees in the entire United Kingdom.
  • Data centers’ 2025 electricity consumption had a water footprint of 4.5 trillion liters of water—enough to fill 1.8 million Olympic-sized pools or meet the annual basic domestic water needs of over 600 million people in Sub-Saharan Africa.
  • The land footprint of 2025 data centers’ electricity demand was 6,900 km2, nearly 4.5 times the size of Greater London.
  • AI workloads accounted for roughly 20% of total data centers’ electricity use in 2025 and are projected to grow to 40% by 2030.
  • If AI’s share of data center energy rises to 40%, electricity consumption could reach 378 TWh—over 9 times the electricity consumption of Nigeria (world’s 6th largest nation by population, with 224 million).
  • Projected global data centers’ electricity consumption could exceed 945 TWh by 2030, accounting for almost 3% of projected global electricity use - enough to supply resi-dential electricity to all 1.3 billion people in Sub-Saharan Africa for about 5.5 years.
  • If treated as a country, 945 TWh would rank 6th globally by electricity consumption.
  • The associated water footprint of projected 2030 electricity consumption of data centers is 9.3 trillion liters, or enough to meet the minimum annual domestic water needs of all 1.3 billion residents of Sub-Saharan Africa for a full year.
  • The associated land footprint of data centers’ expected electricity use in 2030 would be over 14,500 km2, roughly 10 times the size of Mexico City or about twice the Jakarta metropolitan area, home to over 32 million people.
  • The physical lifecycle of AI hardware presents a growing crisis. AI infrastructure could generate up to 2.5 million metric tons of e-waste annually by 2030, equivalent to discarding nearly 250 Eiffel Towers every year.

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